Webinar: Why ERPs Aren’t Enough for Modern AR

In a recent PYMNTS Payments on Air webinar, host John Gaffney, Chief Content Officer at PYMNTS, sat down with two seasoned finance leaders to explore the evolving role of Enterprise Resource Planning (ERP) systems and why they are no longer sufficient on their own to manage and meet the demands of modern accounts receivable (AR) operations.

The discussion featured:

• Jen Ebert, Director of Finance at Papé Group, a heavy equipment and material handling supplier, and
• Lee An Schommer, Chief Product Officer at Billtrust.

Together, they unpacked the growing complexity of AR, the limitations of ERP systems, and how finance teams are leveraging automation and AI to improve cash flow management, AR operational efficiency, and customer experience.

Watch the full webinar replay to hear the complete discussion.

ERP Is the Backbone, Not the Entire AR Solution

ERP systems remain foundational to finance, serving as the system of record for accounting, controls, and compliance. But as receivables processes grow in number and complexity, ERP systems are no longer designed to handle the full scope of AR operations, particularly as teams are more focused not just on B2B payments processing, but rather, financial management and cash flow optimization.

Ebert framed the distinction clearly, noting that ERP systems are built to record transactions, but “modern AR requires far more than that.”

“AR today is much more than recording transactions. It’s a customer engagement model – its collection strategy, dispute management, and how we accelerate cash.”

-Jen Ebert, Director of Finance at Papé Group

From prioritizing collections to predicting payment behavior and improving cash flow forecasts, AR has evolved into a forward-looking discipline. ERP systems provide visibility into the past, while AR automation platforms help finance teams anticipate what happens next and shape what happens next.

Lee An Schommer reinforced this, describing AR automation software as an operational layer that sits on top of ERP systems to deliver real-time intelligence, automation, and insight.

“Your AR platform should give not only insights, but predictions—and that’s often where ERPs fall short.”

-Lee An Schommer, Chief Product Officer at Billtrust

The Hidden Cost of Data Fragmentation and Manual Work

One of the most pressing challenges discussed was data fragmentation and information silos. Many organizations operate across multiple ERP systems which creates disconnected datasets and inefficient processes. Research shows companies manage three ERP systems on average. This fragmentation forces AR teams into manual workarounds that slow operations and reduce effectiveness.

“Collectors are exporting spreadsheets, reconciling reports just to determine what the next steps are,” explained Ebert.

Instead of focusing on collections and customer relationships, teams spend valuable time gathering and reconciling data. The impact is significant:

• Slower cash application
• Reduced visibility into risk
• Delayed decision-making
• Poorer customer experience

“When collections spend their morning pulling data instead of talking to customers, we’re not managing receivables, we’re managing data extraction.”

-Jen Ebert, Director of Finance, Papé Group

For CFOs, the implication is clear: manual processes are not just inefficient; they are a direct barrier when the goal is to optimize cash flow and liquidity. Instead of handling collections reminders and invoice dispute resolutions, AR professionals are handling financial data.

Process Flexibility and Collections Management are Critical in Modern AR

Another key theme was the need for flexibility in AR processes. Unlike ERP systems, which are often rigid and difficult to customize, modern AR requires dynamic workflows that adapt to different customer profiles and risk levels.

“Not every customer should be treated the same way,” said Ebert.

A $20,000 invoice and a $2 million invoice should not follow the same process. High-risk accounts, strategic customers, and chronically delinquent accounts all require tailored approaches. However, building this level of nuance directly into ERP systems is expensive, complex, and difficult to maintain, especially during system upgrades.

“Modern AR automation platforms allow finance teams to adapt processes much faster—without compromising controls.”

-Jen Ebert, Director of Finance, Papé Group

For finance leaders, the takeaway is that agility creates AR process excellence. It’s essential for managing risk, improving collections recovery, and reducing bad debt.

Evaluating AR Automation Solutions: Connectivity, Configurability, and Control

When evaluating AR automation technology, Schommer outlined three essential criteria:

• Connectivity: Seamless integration with a variety of ERP systems
  Integration should be available right out of the box and span ERPs, payment networks, banks, and financial institutions, as well as a large number of AP portals. The best AR automation solutions will also evolve with your ERP system upgrades, never asking you to recertify the AR solution.
• Configurability: Flexible workflows without heavy customization
  Those who chose to use their ERP for AR operations need constant custom coding to tailoring, which can make AR support both difficult and unsustainable.
• Control – Auditability and transparency, especially with AI
  Finance teams need to understand, validate, and trust how decisions are being made, enabling clear oversight, regulatory compliance, and the ability to trace outcomes back to underlying data and clear evidence. Avoid “black box” AI decisioning and look for solutions that provide recommendations backed by defensible evidence. This is particularly critical for CFOs balancing innovation with governance and compliance requirements.

“You don’t want to have to do heroics just to get connected. AR automation should just talk to the data wherever it is,” said Schommer.

Equally important is ensuring that systems are built on best practices rather than blank slates that require heavy internal design and adequate data collection before AI-generated decisions and recommendations can be trusted. Transparency, auditability, and the ability to “trust but verify” remain critical for finance organizations adopting AI.

Schommer explained that leading solutions are pre-built on vast amounts of industry data that drive best practices. An AI model should never start from scratch with zero data. She also warned executives to scrutinize AI claims carefully: “Ask what their large language model is and what it’s built on. Is it generic, or built on proprietary, meaningful data?”

AI in AR: 6 Practical Use Cases that Generate Cash Flow

While AI is a major focus across finance, both speakers emphasized that its value lies in practical application, including:

• Prioritizing collections activities
• Predicting payment timing
• Automating cash application processes
• Drafting customer communications
• Identifying invoice dispute patterns
• Using AR data to improve cash flow forecasting

Knowing when to lean on AI is important but it’s arguably more important to know when not to use it. AI enhances human expertise but doesn’t replace it. Humans remain essential in relationship management and strategic decision-making.

“The goal isn’t fewer decisions. It’s better decisions. AI should eliminate administrative work, not human judgment.”

-Jen Ebert, Director of Finance, Papé Group

Measuring ROI: From DSO to Strategic Impact

When it comes to justifying AR tech investments, hard metrics still matter most. Key performance indicators include:

• Days Sales Outstanding (DSO)
• Days to payment
• Bad debt reduction
• Cost savings from reducing payment processing costs

ROI has been evaluated across the AR industry. According to recent studies:

• 93% of finance leaders confirmed that their AR automation software delivered the ROI they expected
• 95% say AR software delivers greater ROI when compared to native ERP tools for AR
• Billtrust clients report a 384% ROI, on average, with a breakeven in 9 months

“If they can’t give you ROI with data to back it up, question it,” warned Schommer. But as Ebert emphasized, the true value extends beyond hard ROI to strategic benefits such as scalability, customer experience, and organizational agility. AR is ultimately a lever for improving the company’s cash position and enabling growth.

“It’s not just about collections or cash application. It’s about managing liquidity.”

-Jen Ebert, Director of Finance, Papé Group

Key Takeaways for CFOs and AR Leaders

The session concluded with two practical pieces of advice for executives looking to modernize AR:

• AR teams don’t usually have a collection problem — they have a visibility problem. AR teams can’t see cash flow bottlenecks and how to unlock the cash.
• Map where humans are doing manual steps. That’s your opportunity to automate and unlock cash.

In summary:

• ERP systems remain essential, but insufficient for modern AR
• Fragmented data and manual processes are major barriers to efficiency
• Flexible, intelligent AR platforms enable more informed decision-making
• AI delivers value when applied to real-world workflows in AR operations
• The ultimate goal is improved liquidity, not just faster collections

Dive Deeper

To hear the full conversation and explore these insights in more detail, watch the webinar. And don’t miss the research study, ERPs Alone Aren’t Enough: AR Software Required for Predictable Cash Flow.